HHS Public Access Author manuscript Author Manuscript
Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04. Published in final edited form as:
Soc Psychiatry Psychiatr Epidemiol. 2016 October ; 51(10): 1405–1415. doi:10.1007/s00127-016-1229-0.
Marijuana Use from Adolescence to Adulthood: Developmental Trajectories and Their Outcomes Judith S. Brook, Ed.Da,d,1,c, Chenshu Zhang, Ph.D.a,d,c, Carl G. Leukefeld, DSWb, and David W. Brook, M.D.a,d,c
Author Manuscript
aDepartment
of Psychiatry, New York University School of Medicine, New York, New York
bDepartment
of Behavioral Sciences, University of Kentucky, Lexington, KY
of Psychiatry, New York University School of Medicine, 215 Lexington Avenue, 15th Floor, New York, NY 10016 dDepartment
Abstract Background—The study assesses the degree to which individuals in different trajectories of marijuana use are similar or different in terms of unconventional behavior, sensation seeking, emotional dysregulation, nicotine dependence, alcohol dependence/abuse, children living at home, and spouse/partner marijuana use at age 43. Method—This study used a longitudinal design. The sample participants (N=548) were first studied at mean age 14 and last studied at mean age 43.
Author Manuscript
Results—Six trajectories of marijuana use were identified: chronic/heavy users (3.6%), increasing users (5.1%), chronic/occasional users (20%), decreasers (14.3%), quitters (22.5%), and nonusers/experimenters (34.5%). With three exceptions, as compared with being a nonuser/ experimenter, a higher probability of belonging to the chronic/heavy, the increasing, or the chronic/occasional user trajectory group was significantly associated with a greater likelihood of unconventional behavior, sensation seeking, emotional dysregulation, nicotine dependence, alcohol dependence/abuse, having children who lived at home, and having a spouse/partner who used marijuana at early midlife. In addition, compared with being a quitter, a higher probability of belonging to the chronic/heavy user trajectory group was significantly associated with a higher likelihood of unconventional behavior, sensation seeking, emotional dysregulation, alcohol dependence/abuse, and spouse/partner marijuana use. Implications for intervention are presented.
Author Manuscript
Conclusions—Trajectories of marijuana use, especially chronic/heavy use, increasing use, and chronic/occasional use, are associated with unconventional behavior, sensation seeking, emotional dysregulation, nicotine dependence, alcohol dependence/abuse, having children who lived at home, and spouse/partner marijuana use at age 43. The importance of the findings for prevention and treatment programs are discussed.
cNone of the authors have any financial involvement in any organization or entity with a direct financial interest in the subject matter or materials discussed in the manuscript. Reprints and correspondence should be addressed to Dr. Judith S. Brook, Department of Psychiatry, New York University School of Medicine, 215 Lexington Avenue, 15th Floor, New York, NY 10016; [email protected]. On behalf of all authors, the corresponding author states that there is no conflict of interest.
Brook et al.
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Author Manuscript
Keywords Trajectories of marijuana use; unconventional behavior; sensation seeking; emotional dysregulation; nicotine dependence; alcohol dependence/abuse; children living at home; spouse/ partner marijuana use
Introduction
Author Manuscript
Several studies have examined the consequences of marijuana use on adolescent and young adult outcomes (e.g., health outcomes) [1–5]. In general, the findings have demonstrated that chronic marijuana users, compared to non-users, are more likely to demonstrate a number of adverse consequences, including psychiatric disorders [6], poor school achievement [7], financial difficulties [7], and difficulties at work [7]. In comparison, less is known about the adverse consequences of the trajectories of increasing marijuana users, occasional marijuana users, decreasers, and quitters.
Author Manuscript
Operating within a Family Interactional Theory (FIT) [8] and a Life Course framework [9], we focused on important trajectories in substance use (e.g., chronic use and increased use) as they relate to functioning in a variety of areas. For instance, the trajectories of chronic and increasing marijuana use may be associated with drug-prone personality attributes and psychiatric conditions, difficulties in interpersonal relations, and environmental factors, such as financial difficulty [10–14]. In recent years, a number of investigators have attempted to identify the patterns or trajectories of marijuana use [3, 15]. Examination of the trajectories or patterns of use enables the assessment of the consequences of multiple trajectories of marijuana use [16]. The present study adds to the literature by examining the effects of longterm trajectories of marijuana use from age 14 to age 43 on the following outcomes in early midlife. In the personal attribute area, we selected both externalizing and internalizing behaviors as they are both manifestations of personal attributes. We also postulated that certain trajectories of marijuana use would predict nicotine dependence and alcohol dependence/abuse. We further postulated that some trajectories of marijuana use would be associated with unconventional behaviors and ultimately, avoiding having children or children who lived at home. Finally, based on selection theory, we postulated that adults who use marijuana would be more likely to select a spouse/partner who used marijuana.
Author Manuscript
In the present research, we used the growth mixture modeling (GMM) approach to assess trajectories [11, 13, 17, 18]. This approach enabled us to compare multiple trajectories of marijuana use as related to some of the consequences of use (e.g., emotional problems, nicotine dependence, alcohol dependence/abuse). Several researchers have identified the following trajectories of marijuana use: non/experimental use, occasional use, chronic use, increasing use, and quitters [3, 14, 19]. For example, Caldeira et al. (2012) [3] reported that chronic and late-increasing marijuana users had the worst health outcomes, including functional impairment due to injury, illness, or emotion problems. In a sample of African American and Puerto Rican adolescents and adults, chronic marijuana use was associated with increased violence, greater financial instability, and increased sexual risk behavior [10, 16]. In a study using national panel data, Schulenberg and colleagues (2005) [13] reported that chronic marijuana use was related to a greater likelihood of marijuana dependence and Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
Page 3
Author Manuscript
substance abuse. The association of other trajectories of marijuana use with adverse outcomes has been reported in the literature. For example, in terms of mental health in adolescence, Brook, Lee et al. (2011) [16] reported that non-users did not differ from adolescent-limited users in symptoms of depression. A greater understanding of the nature of the trajectories of marijuana use is significant for the timing and targeting of interventions focused on trajectories of use related to adverse outcomes.
Author Manuscript
Our study departs from earlier research which covers a relatively short span of time, but there are some exceptions [3, 17, 20]. In this study, we build on earlier research and assess the long-term patterns of marijuana use as they relate to personal and interpersonal functioning at mean age 43. The current longitudinal study uses data beginning in adolescence and extending to the fifth decade of life. We hypothesize the following: membership in the chronic/heavy use, increasing use, and chronic/occasional use trajectory groups, as compared with the non/experimental use trajectory group, are associated in adulthood with greater unconventional behaviors, emotional problems, sensation seeking, nicotine dependence, alcohol dependence/abuse, avoiding having children or children who lived at home, and having a spouse/partner who was a marijuana user.
Methods Participants and Procedure
Author Manuscript Author Manuscript
Data on the participants in this study came from a community-based random sample residing in one of two upstate New York counties (Albany and Saratoga) first assessed in 1983. The sample was taken from an earlier study using maternal interviews which began in 1975 (T1). The participants’ mothers were interviewed about the participants in 1975 (T1) to assess problem behavior among youngsters. At T1, population data from the census (updated in 1975) for sampling units in Albany and Saratoga counties were obtained. A systematic sample of primary sampling units (blocks) in each county was then drawn with probability proportional to the number of households. At the time the data was collected, the sampled families were generally representative of the population of families in the two upstate New York counties. There was a close match of the participants on family income, maternal education, and family structure with the 1980 census. Mothers with one or more child(ren) in the age range of 1–10 were recruited and, when there were multiple children in the family, one child in that age range was randomly selected. With regards to ethnicity, the children of the sample were 90% White, 8% African American, and 2% other ethnic/racial minorities. Forty nine percent of the children were females. The detailed sampling procedures were published elsewhere [8]. Interviews were conducted in 1983 (T2, N=756), 1985–1986 (T3, N=739), 1992 (T4, N=750), 1997 (T5, N=749), 2002 (T6, N=673), 2007 (T7, N=607), and 2012–2013 (T8, N=548). The mean ages (standard deviations) of participants at the followup interviews were 14.1 (2.8) at T2, 16.3 (2.8) at T3, 22.3 (2.8) at T4, 27.0 (2.8) at T5, 31.9 (2.8) at T6, 36.6 (2.8) at T7, and 43.0 (2.8) at T8, respectively. At T2–T7, extensively trained and supervised lay interviewers administered interviews in private. The T8 data collection involved an Internet-based self-administered questionnaire. Written informed consent was obtained from participants and their mothers in 1983, 1985– 1986, and 1992, and from participants only in 1997, 2002, 2005–2006, and 2012–2013. The Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
Page 4
Author Manuscript
Institutional Review Board of the New York University School of Medicine authorized the use of human subjects in this research study at T8. Earlier waves of the study were approved by the Institutional Review Boards of the Mount Sinai School of Medicine or New York Medical College. Additional information regarding the study methodology is available in prior publications [8]. Measures
Author Manuscript
Marijuana Use—At each time wave (T2–T8), questions about marijuana use (adapted from the Monitoring the Future study [21]) were included. In order to measure the lifetime quantity and frequency of marijuana use from childhood to the mid-thirties, at each time wave questions were asked about the frequency of marijuana use during the period from the last time wave through the current time wave. Specifically, the questions used were the frequency and quantity of marijuana use in childhood and early adolescence for T2 (prior to and at T2), during the past two years in adolescence for T3 (T2–T3), during the past five years in the early twenties for T4 (T3–T4), during the past five years in the late twenties for T5 (T4–T5), during the past five years in the late twenties and early thirties for T6 (T5–T6), during the past five years in the mid-thirties for T7 (T6–T7), and during the past five years in the early-forties for T8 (T7–T8). The marijuana use measure at each point in time had a scale coded as none (0), a few times a year or less (1), once a month (2), several times a month (3), once a week (4), several times a week (5), and daily (6).
Author Manuscript
The dependent variables were assessed in 2012–2013 and consisted of unconventional behaviors (i.e., tolerance of deviance [22], rebellion [23], delinquency [24], and antisocial behaviors [25]), emotional problems [26], sensation seeking [27], nicotine dependence [28], alcohol dependence/abuse [25], children living at home, and spouse/partner marijuana use. Table 1 lists the dependent variables, the number of items comprising each scale, response ranges, sample items, and Cronbach’s alphas. For the indicator variable of high unconventional behaviors, a participant was assigned a score of 1 for the respective indicator variable if at least two of the component scale values were 1 standard deviation (SD) above the mean for that scale, respectively. For the indicator variables of high sensation seeking and high emotional dysregulation, a participant was assigned a score of 1 if the original scale was 1 SD above the sample mean for that scale. For the indicator variable of spouse/partner marijuana use, a participant was assigned a score of 1 if the participant reported that his/her spouse/partner used marijuana at least on 1–2 occasions in the past year (see Table 1 for further descriptions of the original scales).
Author Manuscript
Control variables—The following variables were included as control variables: gender, T8 age, T2 family income in the past year before taxes, T2 highest parental educational level, T2 self-reported grade point average (GPA), T2 depressive mood (5 items, alpha=0.75, e.g., In the past few years, how often have you been bothered by feeling low in energy or slowed down? [29]), T2 delinquency (5 items, alpha=0.65, e.g., How often have you gotten into a serious fight at school or work? [30]), T2 alcohol use [21], and T2 cigarette smoking [21].
Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
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Analysis
Author Manuscript Author Manuscript
Using the Mplus software [31], we conducted GMM analyses to identify the developmental trajectories of marijuana use. As suggested by Bray, Lanza, & Tan (2015) [32], the following demographic variables were included as control variables in the trajectories analyses: gender, T2 age, T2 family income, T2 highest parental educational level, and T2 GPA. We treated the dependent variable (marijuana use at each time point) as a censored normal variable. We applied the full information maximum likelihood (FIML) approach for the missing data in the analysis. We set each of the trajectory polynomials to be cubic. We used the minimum Bayesian Information Criterion (BIC) to determine the number of trajectory groups (G). We did not consider groups with fewer than 3% of the sample because some investigators have cautioned against over-extraction of latent classes due to the presence of non-normal data [33]. After extracting the latent classes, we assigned each participant to the trajectory group with the largest Bayesian posterior probability (BPP). For each of the trajectory groups, we created an indicator variable, which had a value of 1 if participants had the largest BPP for that group and 0 otherwise. The observed trajectory for a group was the average of marijuana use at each time point for participants assigned to the group (see Figure 1).
Author Manuscript
We then conducted separate binary logistic regression analyses to examine the association between marijuana use trajectories and greater unconventional behavior, greater emotional problems, more sensation seeking, nicotine dependence, alcohol dependence/abuse, having children who lived at home, and having spouse/partner who used marijuana, respectively. Because specifying which trajectory group an individual belongs to is subject to error, we used the BPPs of belonging to each trajectory group as the independent variables. Because one group was chosen as the reference, the number of independent trajectory variables was G-1, where G was the number of trajectory groups. We then conducted separate multivariate logistic regression analyses using the following control variables: age, gender, T2 parental educational level, T2 family income, T2 GPA, T2 delinquency, T2 depressive mood, T2 alcohol use, and T2 cigarette smoking.
Results
Author Manuscript
There were no statistically significant differences between participants included in the analyses of adult functioning at T8 (N=548) and the T2 participants who were missing at T8 (N=258) with respect to age (t = 0.17, p-value = 0.86), T2 family income (t = −1.91, p-value = 0.06), T2 depressive mood (t= −0.69, p-value = 0.49), T2 delinquency (t = 1.79, p-value = 0.07), T2 alcohol use (t= −1.57, p-value = 0.12), T2 cigarette smoking (t= −0.02, p-value = 0.98), and T2 marijuana use (t= 0.03, p-value = 0.97). However, there was a greater percentage of female participants (54.7% vs. 36.8%; χ2(1) = 22.55, p-value < 0.001) and a higher parental educational level (13.65 vs. 13.07; t= −3.07, p-value = 0.002) among participants who were included in the T8 analyses, as compared to those who were excluded. Trajectories of Marijuana Use The mean (Standard Deviation) of the marijuana use scores at each time point were 0.56 (1.19), 0.75 (1.35), 1.00 (1.37), 0.94 (1.43), 0.72 (1.37), 0.61 (1.23), and 0.58 (1.26) for T2–
Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
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T8 respectively. The percentage of marijuana users peaked at T4 (mean age=22) and then decreased through T8 (mean age =43). We calculated solutions for the three-group trajectory (Likelihood Value = −5400; BIC = 11008; Entropy = 0.80), the four-group trajectory (Likelihood Value = −5254; BIC = 10782; Entropy = 0.81), the five-group trajectory (Likelihood Value = −5188; BIC = 10717; Entropy = 0.81), and the six-group trajectory (Likelihood Value = −5138; BIC = 10685; Entropy = 0.81). We chose the six-group solution, because the BIC value was lower than those for the five-group trajectory. Participants were then assigned to the marijuana trajectory group that best depicted their marijuana use over time. The average classification probabilities for group membership ranged from 0.84 to 0.90, which indicate a satisfactory classification.
Author Manuscript Author Manuscript
Figure 1 presents the six observed marijuana use trajectories. The trajectory groups were named: chronic/heavy users (N=29, 3.6%), increasing users (N=41, 5.1%), chronic/ occasional users (N=161, 20%), decreasers (N=115, 14.3%), quitters (N=181, 22.5%), and nonusers/experimenters (N=279, 34.5%). As noted in Figure 1, the chronic/heavy users started early, achieved the level of use on a weekly basis in late adolescence (T3), and then stayed at that level through the early forties, the increasing users started late, increased use from late adolescence/emerging adulthood to the early thirties (weekly, several times a week or daily), and then stayed at that level through the early forties. The decreasers started early, achieved the maximum level of use on a monthly basis in late adolescence (T3), and then tapered off gradually. The chronic/occasional users started late and used marijuana less than on a monthly basis, but stayed at that level through the early forties. The quitters started early, tapered off from late adolescence/emerging adulthood into adulthood, and quit completely at mean age 32 (T6). There was a significant association between gender and marijuana trajectory group membership [χ2(5)=34.5, p
Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04. Published in final edited form as:
Soc Psychiatry Psychiatr Epidemiol. 2016 October ; 51(10): 1405–1415. doi:10.1007/s00127-016-1229-0.
Marijuana Use from Adolescence to Adulthood: Developmental Trajectories and Their Outcomes Judith S. Brook, Ed.Da,d,1,c, Chenshu Zhang, Ph.D.a,d,c, Carl G. Leukefeld, DSWb, and David W. Brook, M.D.a,d,c
Author Manuscript
aDepartment
of Psychiatry, New York University School of Medicine, New York, New York
bDepartment
of Behavioral Sciences, University of Kentucky, Lexington, KY
of Psychiatry, New York University School of Medicine, 215 Lexington Avenue, 15th Floor, New York, NY 10016 dDepartment
Abstract Background—The study assesses the degree to which individuals in different trajectories of marijuana use are similar or different in terms of unconventional behavior, sensation seeking, emotional dysregulation, nicotine dependence, alcohol dependence/abuse, children living at home, and spouse/partner marijuana use at age 43. Method—This study used a longitudinal design. The sample participants (N=548) were first studied at mean age 14 and last studied at mean age 43.
Author Manuscript
Results—Six trajectories of marijuana use were identified: chronic/heavy users (3.6%), increasing users (5.1%), chronic/occasional users (20%), decreasers (14.3%), quitters (22.5%), and nonusers/experimenters (34.5%). With three exceptions, as compared with being a nonuser/ experimenter, a higher probability of belonging to the chronic/heavy, the increasing, or the chronic/occasional user trajectory group was significantly associated with a greater likelihood of unconventional behavior, sensation seeking, emotional dysregulation, nicotine dependence, alcohol dependence/abuse, having children who lived at home, and having a spouse/partner who used marijuana at early midlife. In addition, compared with being a quitter, a higher probability of belonging to the chronic/heavy user trajectory group was significantly associated with a higher likelihood of unconventional behavior, sensation seeking, emotional dysregulation, alcohol dependence/abuse, and spouse/partner marijuana use. Implications for intervention are presented.
Author Manuscript
Conclusions—Trajectories of marijuana use, especially chronic/heavy use, increasing use, and chronic/occasional use, are associated with unconventional behavior, sensation seeking, emotional dysregulation, nicotine dependence, alcohol dependence/abuse, having children who lived at home, and spouse/partner marijuana use at age 43. The importance of the findings for prevention and treatment programs are discussed.
cNone of the authors have any financial involvement in any organization or entity with a direct financial interest in the subject matter or materials discussed in the manuscript. Reprints and correspondence should be addressed to Dr. Judith S. Brook, Department of Psychiatry, New York University School of Medicine, 215 Lexington Avenue, 15th Floor, New York, NY 10016; [email protected]. On behalf of all authors, the corresponding author states that there is no conflict of interest.
Brook et al.
Page 2
Author Manuscript
Keywords Trajectories of marijuana use; unconventional behavior; sensation seeking; emotional dysregulation; nicotine dependence; alcohol dependence/abuse; children living at home; spouse/ partner marijuana use
Introduction
Author Manuscript
Several studies have examined the consequences of marijuana use on adolescent and young adult outcomes (e.g., health outcomes) [1–5]. In general, the findings have demonstrated that chronic marijuana users, compared to non-users, are more likely to demonstrate a number of adverse consequences, including psychiatric disorders [6], poor school achievement [7], financial difficulties [7], and difficulties at work [7]. In comparison, less is known about the adverse consequences of the trajectories of increasing marijuana users, occasional marijuana users, decreasers, and quitters.
Author Manuscript
Operating within a Family Interactional Theory (FIT) [8] and a Life Course framework [9], we focused on important trajectories in substance use (e.g., chronic use and increased use) as they relate to functioning in a variety of areas. For instance, the trajectories of chronic and increasing marijuana use may be associated with drug-prone personality attributes and psychiatric conditions, difficulties in interpersonal relations, and environmental factors, such as financial difficulty [10–14]. In recent years, a number of investigators have attempted to identify the patterns or trajectories of marijuana use [3, 15]. Examination of the trajectories or patterns of use enables the assessment of the consequences of multiple trajectories of marijuana use [16]. The present study adds to the literature by examining the effects of longterm trajectories of marijuana use from age 14 to age 43 on the following outcomes in early midlife. In the personal attribute area, we selected both externalizing and internalizing behaviors as they are both manifestations of personal attributes. We also postulated that certain trajectories of marijuana use would predict nicotine dependence and alcohol dependence/abuse. We further postulated that some trajectories of marijuana use would be associated with unconventional behaviors and ultimately, avoiding having children or children who lived at home. Finally, based on selection theory, we postulated that adults who use marijuana would be more likely to select a spouse/partner who used marijuana.
Author Manuscript
In the present research, we used the growth mixture modeling (GMM) approach to assess trajectories [11, 13, 17, 18]. This approach enabled us to compare multiple trajectories of marijuana use as related to some of the consequences of use (e.g., emotional problems, nicotine dependence, alcohol dependence/abuse). Several researchers have identified the following trajectories of marijuana use: non/experimental use, occasional use, chronic use, increasing use, and quitters [3, 14, 19]. For example, Caldeira et al. (2012) [3] reported that chronic and late-increasing marijuana users had the worst health outcomes, including functional impairment due to injury, illness, or emotion problems. In a sample of African American and Puerto Rican adolescents and adults, chronic marijuana use was associated with increased violence, greater financial instability, and increased sexual risk behavior [10, 16]. In a study using national panel data, Schulenberg and colleagues (2005) [13] reported that chronic marijuana use was related to a greater likelihood of marijuana dependence and Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
Page 3
Author Manuscript
substance abuse. The association of other trajectories of marijuana use with adverse outcomes has been reported in the literature. For example, in terms of mental health in adolescence, Brook, Lee et al. (2011) [16] reported that non-users did not differ from adolescent-limited users in symptoms of depression. A greater understanding of the nature of the trajectories of marijuana use is significant for the timing and targeting of interventions focused on trajectories of use related to adverse outcomes.
Author Manuscript
Our study departs from earlier research which covers a relatively short span of time, but there are some exceptions [3, 17, 20]. In this study, we build on earlier research and assess the long-term patterns of marijuana use as they relate to personal and interpersonal functioning at mean age 43. The current longitudinal study uses data beginning in adolescence and extending to the fifth decade of life. We hypothesize the following: membership in the chronic/heavy use, increasing use, and chronic/occasional use trajectory groups, as compared with the non/experimental use trajectory group, are associated in adulthood with greater unconventional behaviors, emotional problems, sensation seeking, nicotine dependence, alcohol dependence/abuse, avoiding having children or children who lived at home, and having a spouse/partner who was a marijuana user.
Methods Participants and Procedure
Author Manuscript Author Manuscript
Data on the participants in this study came from a community-based random sample residing in one of two upstate New York counties (Albany and Saratoga) first assessed in 1983. The sample was taken from an earlier study using maternal interviews which began in 1975 (T1). The participants’ mothers were interviewed about the participants in 1975 (T1) to assess problem behavior among youngsters. At T1, population data from the census (updated in 1975) for sampling units in Albany and Saratoga counties were obtained. A systematic sample of primary sampling units (blocks) in each county was then drawn with probability proportional to the number of households. At the time the data was collected, the sampled families were generally representative of the population of families in the two upstate New York counties. There was a close match of the participants on family income, maternal education, and family structure with the 1980 census. Mothers with one or more child(ren) in the age range of 1–10 were recruited and, when there were multiple children in the family, one child in that age range was randomly selected. With regards to ethnicity, the children of the sample were 90% White, 8% African American, and 2% other ethnic/racial minorities. Forty nine percent of the children were females. The detailed sampling procedures were published elsewhere [8]. Interviews were conducted in 1983 (T2, N=756), 1985–1986 (T3, N=739), 1992 (T4, N=750), 1997 (T5, N=749), 2002 (T6, N=673), 2007 (T7, N=607), and 2012–2013 (T8, N=548). The mean ages (standard deviations) of participants at the followup interviews were 14.1 (2.8) at T2, 16.3 (2.8) at T3, 22.3 (2.8) at T4, 27.0 (2.8) at T5, 31.9 (2.8) at T6, 36.6 (2.8) at T7, and 43.0 (2.8) at T8, respectively. At T2–T7, extensively trained and supervised lay interviewers administered interviews in private. The T8 data collection involved an Internet-based self-administered questionnaire. Written informed consent was obtained from participants and their mothers in 1983, 1985– 1986, and 1992, and from participants only in 1997, 2002, 2005–2006, and 2012–2013. The Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
Page 4
Author Manuscript
Institutional Review Board of the New York University School of Medicine authorized the use of human subjects in this research study at T8. Earlier waves of the study were approved by the Institutional Review Boards of the Mount Sinai School of Medicine or New York Medical College. Additional information regarding the study methodology is available in prior publications [8]. Measures
Author Manuscript
Marijuana Use—At each time wave (T2–T8), questions about marijuana use (adapted from the Monitoring the Future study [21]) were included. In order to measure the lifetime quantity and frequency of marijuana use from childhood to the mid-thirties, at each time wave questions were asked about the frequency of marijuana use during the period from the last time wave through the current time wave. Specifically, the questions used were the frequency and quantity of marijuana use in childhood and early adolescence for T2 (prior to and at T2), during the past two years in adolescence for T3 (T2–T3), during the past five years in the early twenties for T4 (T3–T4), during the past five years in the late twenties for T5 (T4–T5), during the past five years in the late twenties and early thirties for T6 (T5–T6), during the past five years in the mid-thirties for T7 (T6–T7), and during the past five years in the early-forties for T8 (T7–T8). The marijuana use measure at each point in time had a scale coded as none (0), a few times a year or less (1), once a month (2), several times a month (3), once a week (4), several times a week (5), and daily (6).
Author Manuscript
The dependent variables were assessed in 2012–2013 and consisted of unconventional behaviors (i.e., tolerance of deviance [22], rebellion [23], delinquency [24], and antisocial behaviors [25]), emotional problems [26], sensation seeking [27], nicotine dependence [28], alcohol dependence/abuse [25], children living at home, and spouse/partner marijuana use. Table 1 lists the dependent variables, the number of items comprising each scale, response ranges, sample items, and Cronbach’s alphas. For the indicator variable of high unconventional behaviors, a participant was assigned a score of 1 for the respective indicator variable if at least two of the component scale values were 1 standard deviation (SD) above the mean for that scale, respectively. For the indicator variables of high sensation seeking and high emotional dysregulation, a participant was assigned a score of 1 if the original scale was 1 SD above the sample mean for that scale. For the indicator variable of spouse/partner marijuana use, a participant was assigned a score of 1 if the participant reported that his/her spouse/partner used marijuana at least on 1–2 occasions in the past year (see Table 1 for further descriptions of the original scales).
Author Manuscript
Control variables—The following variables were included as control variables: gender, T8 age, T2 family income in the past year before taxes, T2 highest parental educational level, T2 self-reported grade point average (GPA), T2 depressive mood (5 items, alpha=0.75, e.g., In the past few years, how often have you been bothered by feeling low in energy or slowed down? [29]), T2 delinquency (5 items, alpha=0.65, e.g., How often have you gotten into a serious fight at school or work? [30]), T2 alcohol use [21], and T2 cigarette smoking [21].
Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
Page 5
Analysis
Author Manuscript Author Manuscript
Using the Mplus software [31], we conducted GMM analyses to identify the developmental trajectories of marijuana use. As suggested by Bray, Lanza, & Tan (2015) [32], the following demographic variables were included as control variables in the trajectories analyses: gender, T2 age, T2 family income, T2 highest parental educational level, and T2 GPA. We treated the dependent variable (marijuana use at each time point) as a censored normal variable. We applied the full information maximum likelihood (FIML) approach for the missing data in the analysis. We set each of the trajectory polynomials to be cubic. We used the minimum Bayesian Information Criterion (BIC) to determine the number of trajectory groups (G). We did not consider groups with fewer than 3% of the sample because some investigators have cautioned against over-extraction of latent classes due to the presence of non-normal data [33]. After extracting the latent classes, we assigned each participant to the trajectory group with the largest Bayesian posterior probability (BPP). For each of the trajectory groups, we created an indicator variable, which had a value of 1 if participants had the largest BPP for that group and 0 otherwise. The observed trajectory for a group was the average of marijuana use at each time point for participants assigned to the group (see Figure 1).
Author Manuscript
We then conducted separate binary logistic regression analyses to examine the association between marijuana use trajectories and greater unconventional behavior, greater emotional problems, more sensation seeking, nicotine dependence, alcohol dependence/abuse, having children who lived at home, and having spouse/partner who used marijuana, respectively. Because specifying which trajectory group an individual belongs to is subject to error, we used the BPPs of belonging to each trajectory group as the independent variables. Because one group was chosen as the reference, the number of independent trajectory variables was G-1, where G was the number of trajectory groups. We then conducted separate multivariate logistic regression analyses using the following control variables: age, gender, T2 parental educational level, T2 family income, T2 GPA, T2 delinquency, T2 depressive mood, T2 alcohol use, and T2 cigarette smoking.
Results
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There were no statistically significant differences between participants included in the analyses of adult functioning at T8 (N=548) and the T2 participants who were missing at T8 (N=258) with respect to age (t = 0.17, p-value = 0.86), T2 family income (t = −1.91, p-value = 0.06), T2 depressive mood (t= −0.69, p-value = 0.49), T2 delinquency (t = 1.79, p-value = 0.07), T2 alcohol use (t= −1.57, p-value = 0.12), T2 cigarette smoking (t= −0.02, p-value = 0.98), and T2 marijuana use (t= 0.03, p-value = 0.97). However, there was a greater percentage of female participants (54.7% vs. 36.8%; χ2(1) = 22.55, p-value < 0.001) and a higher parental educational level (13.65 vs. 13.07; t= −3.07, p-value = 0.002) among participants who were included in the T8 analyses, as compared to those who were excluded. Trajectories of Marijuana Use The mean (Standard Deviation) of the marijuana use scores at each time point were 0.56 (1.19), 0.75 (1.35), 1.00 (1.37), 0.94 (1.43), 0.72 (1.37), 0.61 (1.23), and 0.58 (1.26) for T2–
Soc Psychiatry Psychiatr Epidemiol. Author manuscript; available in PMC 2016 October 04.
Brook et al.
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T8 respectively. The percentage of marijuana users peaked at T4 (mean age=22) and then decreased through T8 (mean age =43). We calculated solutions for the three-group trajectory (Likelihood Value = −5400; BIC = 11008; Entropy = 0.80), the four-group trajectory (Likelihood Value = −5254; BIC = 10782; Entropy = 0.81), the five-group trajectory (Likelihood Value = −5188; BIC = 10717; Entropy = 0.81), and the six-group trajectory (Likelihood Value = −5138; BIC = 10685; Entropy = 0.81). We chose the six-group solution, because the BIC value was lower than those for the five-group trajectory. Participants were then assigned to the marijuana trajectory group that best depicted their marijuana use over time. The average classification probabilities for group membership ranged from 0.84 to 0.90, which indicate a satisfactory classification.
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Figure 1 presents the six observed marijuana use trajectories. The trajectory groups were named: chronic/heavy users (N=29, 3.6%), increasing users (N=41, 5.1%), chronic/ occasional users (N=161, 20%), decreasers (N=115, 14.3%), quitters (N=181, 22.5%), and nonusers/experimenters (N=279, 34.5%). As noted in Figure 1, the chronic/heavy users started early, achieved the level of use on a weekly basis in late adolescence (T3), and then stayed at that level through the early forties, the increasing users started late, increased use from late adolescence/emerging adulthood to the early thirties (weekly, several times a week or daily), and then stayed at that level through the early forties. The decreasers started early, achieved the maximum level of use on a monthly basis in late adolescence (T3), and then tapered off gradually. The chronic/occasional users started late and used marijuana less than on a monthly basis, but stayed at that level through the early forties. The quitters started early, tapered off from late adolescence/emerging adulthood into adulthood, and quit completely at mean age 32 (T6). There was a significant association between gender and marijuana trajectory group membership [χ2(5)=34.5, p
